New results on web caching with request reordering

We study web caching with request reordering. The goal is to maintain a cache of web documents so that a sequence of requests can be served at low cost. To improve cache hit rates, a limited reordering of requests is allowed. Feder et al., who recently introduced this problem, considered caches of size 1, i.e. a cache can store one document. They presented an offline algorithm based on dynamic programming as well as online algorithms that achieve constant factor competitive ratios. For arbitrary cache sizes, Feder et al. gave online strategies that have nearly optimal competitive ratios in several cost models. In this paper we first present a deterministic online algorithm that achieves an optimal competitiveness, for the most general cost model and all cache sizes. We then investigate the offline problem, which is NP-hard in general. We develop the first polynomial time algorithms that can manage arbitrary cache sizes. Our strategies achieve small constant factor approximation ratios. The algorithms are based on a general technique that reduces web caching with request reordering to a problem of computing batched service schedules. Our approximation result for the Fault Model also improves upon the best previous approximation guarantee known for web caching without request reordering.